Distributed generation and shunt capacitor allocation in radial distribution power networks using a hybrid optimization approach.

This article proposes a new hybrid approach for determining the optimal locations and sizes of distributed generation (DG) and shunt capacitor (SC) units in a radial distribution power network (RPDN). The hybrid framework is introduced, integrating the global search competency of the Whale Optimizer Algorithm (WOA) with the local search proficiency of the Osprey Optimizer Algorithm (OOA) to achieve a better quality solution for the simultaneous DG/SC allocation problem. The hybrid technique assesses its efficacy for different combinations of DG and SC unit allocations on the different-sized RDPNs, including 33-bus, 69-bus, and 118-bus benchmark systems. The optimization problem is solved for single- and multi-objective functions addressing active power loss (APL) reduction, bus voltage (BV) improvement, and operating cost reduction. For a single unit of DG and SC placement, the APL of the 33-bus RDPN is minimized by 77.29%. In contrast, the second combination involving two units of DG/SC placement achieves a PL reduction of 89.61%. Likewise, the first and second combinations of simultaneous DG/SC integration in the 69-bus RDPN yield 52.67% and 74.97% of APL reduction, respectively. Further, the application of the hybrid algorithm is investigated on the 118-bus RPDN for evaluating its effectiveness and scalability to large power networks. Additionally, for multi-objective problems, the optimized single-unit DG/SC allocation inside the 69-bus RDPN reduces the power losses (PL) by 55.70% and enhances minimum BV to 0.9686 per unit for the operational cost of $15266.78. Moreover, the proposed Hybrid Whale- Osprey Algorithm (HWOA) effectively addressed the load uncertainty in the 69-bus RDPN, minimizing the PL and enhancing the BV above the critical value. The quantitative simulation findings showcase the better PL reduction compared to similar works addressed in the literature, demonstrating the benefits of integrating the exploration and exploitation behaviors of WOA and OOA.